- A
Use Durable Functions to orchestrate the processing and enforce ordering.
Why wrong: Adds unnecessary complexity; Event Hubs partition ordering is sufficient.
- B
Increase the 'maxEventBatchSize' setting to 100 in the host.json file to improve throughput.
Why wrong: Larger batch size increases parallelism, risking out-of-order processing.
- C
Set the 'maxEventBatchSize' to 1 in the host.json file to process one event at a time per instance.
Ensures sequential processing per partition, preserving order.
- D
Use a different partition key such as a unique trade ID to distribute load evenly.
Why wrong: Breaks ordering for same stock symbol.
AZ-204 Develop Azure compute solutions Practice Question
This AZ-204 practice question tests your understanding of develop azure compute solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are a developer at a financial services company. You need to design a solution for processing real-time stock trade data. The system receives thousands of trades per second from an on-premises system. Each trade must be validated, enriched with reference data, and then stored in a data lake for analytics. You have the following requirements: - The processing must be serverless and scale automatically with high throughput. - The enrichment step requires calling an external REST API that can handle up to 100 requests per second. If the API is overwhelmed, trades must be retried with exponential backoff. - The solution must minimize cost and operational overhead. - Trades must be processed in order per stock symbol. You provision an Azure Event Hubs namespace with a single event hub. Trades are sent to the event hub with the stock symbol as the partition key. You configure an Azure Functions app with an Event Hubs trigger to process events. The function validates, enriches by calling the external API, and writes the enriched trade to Azure Data Lake Storage. During testing, you notice that some trades are processed out of order for the same stock symbol when the external API throttles requests. What should you do to ensure ordering per stock symbol?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Set the 'maxEventBatchSize' to 1 in the host.json file to process one event at a time per instance.
Option D is correct. To maintain ordering per stock symbol, you need to ensure that all events for a given symbol are processed by a single function instance. Event Hubs partitions guarantee ordering within a partition. By using the stock symbol as the partition key, all trades for the same symbol go to the same partition. However, if the function scales out to multiple instances, the Event Hubs trigger may distribute partitions across instances, but each partition is processed by only one instance at a time. The issue is that when the external API throttles, the function may retry the event, but during the retry, other events from the same partition might be processed by the same instance out of order if the function does not wait for the retry to complete before processing next events. By setting 'maxEventBatchSize' to 1 in the host.json, you ensure that only one event is processed at a time per function instance, preventing out-of-order processing. Option A is wrong because increasing batch size would increase concurrency and worsen ordering. Option B is wrong because Durable Functions add complexity and are not needed for simple ordering. Option C is wrong because using a different partition key would scatter events for the same symbol across partitions, breaking ordering.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Durable Functions to orchestrate the processing and enforce ordering.
Why it's wrong here
Adds unnecessary complexity; Event Hubs partition ordering is sufficient.
- ✗
Increase the 'maxEventBatchSize' setting to 100 in the host.json file to improve throughput.
Why it's wrong here
Larger batch size increases parallelism, risking out-of-order processing.
- ✓
Set the 'maxEventBatchSize' to 1 in the host.json file to process one event at a time per instance.
Why this is correct
Ensures sequential processing per partition, preserving order.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a different partition key such as a unique trade ID to distribute load evenly.
Why it's wrong here
Breaks ordering for same stock symbol.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which AZ-204 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this AZ-204 question test?
Develop Azure compute solutions — This question tests Develop Azure compute solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set the 'maxEventBatchSize' to 1 in the host.json file to process one event at a time per instance. — Option D is correct. To maintain ordering per stock symbol, you need to ensure that all events for a given symbol are processed by a single function instance. Event Hubs partitions guarantee ordering within a partition. By using the stock symbol as the partition key, all trades for the same symbol go to the same partition. However, if the function scales out to multiple instances, the Event Hubs trigger may distribute partitions across instances, but each partition is processed by only one instance at a time. The issue is that when the external API throttles, the function may retry the event, but during the retry, other events from the same partition might be processed by the same instance out of order if the function does not wait for the retry to complete before processing next events. By setting 'maxEventBatchSize' to 1 in the host.json, you ensure that only one event is processed at a time per function instance, preventing out-of-order processing. Option A is wrong because increasing batch size would increase concurrency and worsen ordering. Option B is wrong because Durable Functions add complexity and are not needed for simple ordering. Option C is wrong because using a different partition key would scatter events for the same symbol across partitions, breaking ordering.
What should I do if I get this AZ-204 question wrong?
Identify which AZ-204 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 21, 2026
This AZ-204 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AZ-204 exam.
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